Bulk Synchronous Parallelism (BSP) is a parallel programming model that abstracts from low-level program structures in favour of supersteps. A superstep consists of a set of independent local computations, followed by a global communication phase and a barrier synchronisation. Structuring programs in this way enables their costs to be accurately determined from a few simple architectural parameters, namely the permeability of the communication network to uniformly-random traffic and the time to synchronise. Although permutation routing and barrier synchronisations are widely regarded as inherently expensive, this is not the case. As a result, the structure imposed by BSP comes for free in performance terms, while bringing considerable benefits from an application-building perspective. This paper answers the most common questions we are asked about BSP and justifies its claim to be a major step forward in parallel programming. 1 Why is another model needed? In the 1980s a large number ...

The Bulk Synchronous Parallel (BSP) model provides a theoretical framework to accurately predict the execution time of parallel programs. In this paper we describe a BSP programming library that has been developed, and contrast two approaches to analysing performance: (1) a pencil and paper method with a theoretical cost model; (2) a profiling tool that analyses trace information generated during program execution. These approaches are evaluated on an industrial application code that solves fluid dynamics equations around a complex aircraft geometry on an IBM SP2 and SGI PowerChallenge. We show how the tool can be used to explore the communication patterns of the CFD code and accurately predict the performance of the application on any parallel machine. 1 Introduction The efficient implementation of complex algorithms onto parallel machines is an arduous task. Furthermore, the resulting performance is often only known once this task has been completed. This is unsatisfactory consideri...

Parallel computers have been successfully deployed in many scientific and numerical application areas, although their use in non-numerical and database applications has been scarce. In this report, we first survey the architectural advancements beginning to make general-purpose parallel computing cost-effective, the requirements for non-numerical (or symbolic) applications, and the previous attempts to develop parallel databases. The central theme of the Bulk Synchronous Parallel model is to provide a high level abstraction of parallel computing hardware whilst providing a realisation of a parallel programming model that enables architecture independent programs to deliver scalable performance on diverse hardware platforms. Therefore, the primary objective of this report is to investigate the feasibility of developing a portable, scalable, parallel object database, based on the Bulk Synchronous Parallel model of computation. In particular, we devise a way of providing high-level abstra...

The METR technical reports are published as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

: In this paper we present the results of an investigation into parallel implementations of fractal image compression algorithms. In particular, the research addressed the applicability for this purpose of the new Bulk Synchronous Parallel model, as implemented by the Oxford BSP Toolkit. BSP provides a scalable and predictable framework for developing parallel software, with a reliable and straightforward cost model. We take advantage of this model to arrive at an optimal parallel fractal image compression algorithm. 1. Introduction Although the theory of fractals has been around for quite a while now, and its application in image compression investigated by many researchers, advances in the area of fractal image compression have been rather modest compared to other "lossy" compression methods. The weakest point of fractal compression is its very high computational demands. Given that compression ratios and Signal-toNoise (SNR) ratios obtainable with this method are similar to ...

In this paper we design and analyse parallel algorithms with the goal to get exact bounds on their speed-ups on real machines. For this purpose we define an extension of Valiant's BSP model, BSP*, that rewards blockwise communication, and use Valiant's notion of 1-optimality. Intuitively, a 1-optimal parallel algorithm for p processors achieves speed-up close to p. We consider the Multisearch Problem: Assume a strip in 2D to be partitioned into m segments. Given n query points in the strip, the task is to locate, for each query, its segment. For m n p we present a deterministic BSP* algorithm that is 1-optimal, if n p log 2 n. For m ? n p, we present a randomized BSP* algorithm that is 1-optimal with high probability, if m 2 p and n p log 3 n. Both results hold for a wide range of BSP* parameters where the range becomes larger with growing input size n. We further report on implementation work. Previous parallel algorithms for Multisearch were far away from being 1-op...

The diverse architectural features of parallel computers, and the lack of commonly accepted parallel-programming environments, meant that software development for these systems has been significantly more difficult than the sequential case. Until better approaches are developed, the programming environment will remain a serious obstacle to mainstream scalable parallel computing. The work reported in this paper attempts to integrate architectureindependent scalable parallel programming in the Bulk Synchronous Parallel (BSP) model with the shared-memory parallel programming using the theoretical PRAM model. We start with a discussion of problem parallelism, that is, the parallelism inherent to a problem instead of a specific algorithm, and the parallel-programming techniques that allow the capture of this notion. We then review the ubiquitous PRAM model in terms of the model's pragmatic limitations, where particular attention is paid to simulations on practical machines. The BSP model i...

We report the complexity of the solution of triangular systems in parallel. We focus on determining which types of data layouts yield best results, under the assumptions of the BSP model. The Bulk Synchronous Parallel (BSP) model has been provided to play the same part as the traditional von Neumann model for sequential computation: a unifying abstraction of a general purpose computer which can serve as an effective target for a variety of high level programming languages, while being efficiently realisable by a variety of hardware architectures. The study presented here points out that the usual distribution strategies, block row/column contiguous and block row/column wrapped have the same asymptotic complexity. Other data layouts are also studied and compared with the optimum BSP algorithm for solving triangular linear systems. Some experimental results obtained on a Convex SPP1000 and an IBM SP2 are included. The results reported in this paper seem to lead to the conclu...